In contrast to typical semantic relations between verbs, such as antonymy, synonymy or hyponymy, presupposition is a lexical relation that is not very well covered in existing lexical resources. It is also understudied in the field of corpus-based methods of learning semantic relations. Yet, presupposition is a lexical relation that is very important for semantic and discourse analysis tasks – especially regarding the implicit information conveyed by presupposition trigger verbs. In this paper we present a corpus-based method for learning presupposition relations between verbs, embedded in a discriminative classification approach for fine-grained semantic relations. The present paper focuses on important methodological aspects of our work: a discriminative analysis of the semantic properties of the chosen set of relations, the selection of features for classification and design decisions regarding the annotation of fine-grained semantic relations between verbs. We report first results for automatic classification of our target set of fine-grained semantic relations.